Results (PhD Chapter 2)

This series of files compile all analyses done during Chapter 2:

All analyses have been done with R 3.6.2.

Click on the table of contents in the left margin to assess a specific analysis.
Click on a figure to zoom it

To assess Section 1, click here.
To go back to the summary page, click here.

Human activities considered for the analyses:

Data is also available for the number of captured individuals for dogwhelk (Buccinum sp.), common crab (Cancer irroratus), snowcrab (Chinoecetes opilio), nordic shrimp (Pandalus borealis), arctic surfclam (Mactromeris polynyma) and american lobster (Homarus americanus) fisheries.

1. Explorations

1.1. Relationships between parameters

This section explores relationships between each pair of parameters or AH distances.

Fist, we can compute the Spearman’s correlation between each parameter.

Correlation coefficients between habitat parameters and metals concentrations
  om gravel sand silt clay arsenic cadmium chromium copper iron manganese mercury lead zinc S N H J city dredging_collect dredging_dump industry mooring sewers_rain sewers_waste wharves_city wharves_industry CI
om 1 -0.379 -0.708 0.68 0.023 0.423 0.409 0.399 0.388 0.455 0.514 0.438 0.422 0.369 -0.022 -0.121 0.124 0.136 -0.005 0.378 0.335 0.236 0.514 0.233 0.396 -0.052 0.354 0.365
gravel -0.379 1 0.186 -0.471 0.099 -0.077 -0.133 -0.102 -0.127 -0.148 -0.153 -0.184 -0.093 -0.113 0.032 0.007 0.013 0.07 -0.071 -0.15 -0.134 -0.18 -0.218 0.026 -0.052 -0.064 -0.163 -0.131
sand -0.708 0.186 1 -0.788 -0.308 -0.577 -0.5 -0.488 -0.428 -0.372 -0.5 -0.623 -0.576 -0.466 0.053 0.083 0.026 -0.026 0.251 -0.145 -0.147 0.006 -0.421 -0.301 -0.473 0.301 -0.152 -0.164
silt 0.68 -0.471 -0.788 1 0.05 0.455 0.453 0.381 0.345 0.286 0.413 0.557 0.474 0.374 -0.044 -0.011 -0.062 -0.057 -0.134 0.16 0.139 0.029 0.424 0.228 0.388 -0.18 0.156 0.169
clay 0.023 0.099 -0.308 0.05 1 0.18 0.15 0.177 0.103 0.093 0.165 0.054 0.139 0.123 -0.101 -0.076 -0.042 0.021 -0.021 0.033 0.009 0.01 0.007 0.246 0.244 -0.03 0.037 0.097
arsenic 0.423 -0.077 -0.577 0.455 0.18 1 0.736 0.833 0.814 0.775 0.85 0.679 0.9 0.829 -0.195 -0.002 -0.274 -0.186 -0.149 0.396 0.186 0.218 0.66 0.627 0.745 -0.193 0.385 0.45
cadmium 0.409 -0.133 -0.5 0.453 0.15 0.736 1 0.816 0.71 0.583 0.746 0.689 0.846 0.822 -0.339 -0.073 -0.361 -0.154 0.044 0.177 -0.157 -0.012 0.565 0.575 0.727 -0.094 0.101 0.294
chromium 0.399 -0.102 -0.488 0.381 0.177 0.833 0.816 1 0.908 0.818 0.919 0.724 0.907 0.935 -0.31 -0.03 -0.381 -0.221 0.035 0.424 0.011 0.222 0.637 0.668 0.789 -0.048 0.343 0.487
copper 0.388 -0.127 -0.428 0.345 0.103 0.814 0.71 0.908 1 0.85 0.843 0.639 0.895 0.963 -0.262 -0.01 -0.344 -0.241 0.195 0.598 0.175 0.409 0.661 0.654 0.728 0.151 0.516 0.643
iron 0.455 -0.148 -0.372 0.286 0.093 0.775 0.583 0.818 0.85 1 0.87 0.462 0.729 0.808 -0.301 -0.144 -0.279 -0.088 0.133 0.651 0.28 0.488 0.586 0.594 0.636 0.097 0.608 0.664
manganese 0.514 -0.153 -0.5 0.413 0.165 0.85 0.746 0.919 0.843 0.87 1 0.606 0.829 0.831 -0.307 -0.112 -0.287 -0.091 0.047 0.559 0.246 0.391 0.732 0.698 0.824 -0.022 0.516 0.611
mercury 0.438 -0.184 -0.623 0.557 0.054 0.679 0.689 0.724 0.639 0.462 0.606 1 0.805 0.706 -0.156 0.062 -0.264 -0.234 -0.241 0.172 -0.072 -0.031 0.52 0.395 0.594 -0.309 0.122 0.18
lead 0.422 -0.093 -0.576 0.474 0.139 0.9 0.846 0.907 0.895 0.729 0.829 0.805 1 0.93 -0.258 -0.005 -0.348 -0.239 -0.034 0.422 0.111 0.223 0.658 0.681 0.813 -0.108 0.371 0.483
zinc 0.369 -0.113 -0.466 0.374 0.123 0.829 0.822 0.935 0.963 0.808 0.831 0.706 0.93 1 -0.276 -0.003 -0.359 -0.244 0.14 0.462 0.026 0.252 0.641 0.659 0.758 0.067 0.369 0.532
S -0.022 0.032 0.053 -0.044 -0.101 -0.195 -0.339 -0.31 -0.262 -0.301 -0.307 -0.156 -0.258 -0.276 1 0.559 0.704 -0.05 -0.149 -0.196 0.035 -0.105 -0.253 -0.305 -0.329 -0.071 -0.14 -0.241
N -0.121 0.007 0.083 -0.011 -0.076 -0.002 -0.073 -0.03 -0.01 -0.144 -0.112 0.062 -0.005 -0.003 0.559 1 -0.046 -0.684 -0.066 -0.14 -0.143 -0.15 -0.021 -0.107 -0.067 -0.059 -0.177 -0.142
H 0.124 0.013 0.026 -0.062 -0.042 -0.274 -0.361 -0.381 -0.344 -0.279 -0.287 -0.264 -0.348 -0.359 0.704 -0.046 1 0.599 -0.093 -0.074 0.211 0.052 -0.245 -0.302 -0.333 -0.009 0.008 -0.161
J 0.136 0.07 -0.026 -0.057 0.021 -0.186 -0.154 -0.221 -0.241 -0.088 -0.091 -0.234 -0.239 -0.244 -0.05 -0.684 0.599 1 0.012 0.01 0.167 0.103 -0.131 -0.105 -0.148 0.029 0.079 -0.033
city -0.005 -0.071 0.251 -0.134 -0.021 -0.149 0.044 0.035 0.195 0.133 0.047 -0.241 -0.034 0.14 -0.149 -0.066 -0.093 0.012 1 0.414 0.107 0.253 0.324 0.329 0.18 0.969 0.254 0.563
dredging_collect 0.378 -0.15 -0.145 0.16 0.033 0.396 0.177 0.424 0.598 0.651 0.559 0.172 0.422 0.462 -0.196 -0.14 -0.074 0.01 0.414 1 0.743 0.895 0.589 0.585 0.554 0.467 0.95 0.942
dredging_dump 0.335 -0.134 -0.147 0.139 0.009 0.186 -0.157 0.011 0.175 0.28 0.246 -0.072 0.111 0.026 0.035 -0.143 0.211 0.167 0.107 0.743 1 0.791 0.351 0.267 0.268 0.213 0.824 0.642
industry 0.236 -0.18 0.006 0.029 0.01 0.218 -0.012 0.222 0.409 0.488 0.391 -0.031 0.223 0.252 -0.105 -0.15 0.052 0.103 0.253 0.895 0.791 1 0.31 0.431 0.349 0.346 0.946 0.79
mooring 0.514 -0.218 -0.421 0.424 0.007 0.66 0.565 0.637 0.661 0.586 0.732 0.52 0.658 0.641 -0.253 -0.021 -0.245 -0.131 0.324 0.589 0.351 0.31 1 0.581 0.76 0.265 0.457 0.679
sewers_rain 0.233 0.026 -0.301 0.228 0.246 0.627 0.575 0.668 0.654 0.594 0.698 0.395 0.681 0.659 -0.305 -0.107 -0.302 -0.105 0.329 0.585 0.267 0.431 0.581 1 0.893 0.284 0.551 0.722
sewers_waste 0.396 -0.052 -0.473 0.388 0.244 0.745 0.727 0.789 0.728 0.636 0.824 0.594 0.813 0.758 -0.329 -0.067 -0.333 -0.148 0.18 0.554 0.268 0.349 0.76 0.893 1 0.087 0.482 0.659
wharves_city -0.052 -0.064 0.301 -0.18 -0.03 -0.193 -0.094 -0.048 0.151 0.097 -0.022 -0.309 -0.108 0.067 -0.071 -0.059 -0.009 0.029 0.969 0.467 0.213 0.346 0.265 0.284 0.087 1 0.338 0.588
wharves_industry 0.354 -0.163 -0.152 0.156 0.037 0.385 0.101 0.343 0.516 0.608 0.516 0.122 0.371 0.369 -0.14 -0.177 0.008 0.079 0.254 0.95 0.824 0.946 0.457 0.551 0.482 0.338 1 0.873
CI 0.365 -0.131 -0.164 0.169 0.097 0.45 0.294 0.487 0.643 0.664 0.611 0.18 0.483 0.532 -0.241 -0.142 -0.161 -0.033 0.563 0.942 0.642 0.79 0.679 0.722 0.659 0.588 0.873 1

For the regressions, several types of models were considered: linear, quadratic, exponential and logarithmic. Only linear and quadratic models were implemented as there are some bugs with the calculation of the others. The model with the highest \(R^{2}\) is presented on each plot.

OM

Gravel

Sand

Silt

Clay

Arsenic

Cadmium

Chromium

Copper

Iron

Manganese

Mercury

Lead

Zinc

S

N

H

J

CityInf

InduInf

DredColl

DredDump

MoorSite

RainSew

WastSew

CityWha

InduWha

Cumulative Influence

1.2. Species abundances by cumulative influence group

Quitting from lines 301-355 (C2_analyses_B.Rmd) Error in pandoc.table.return(…) : Wrong number of parameters (11 instead of 12) passed: justify De plus : Warning messages: 1: attribute variables are assumed to be spatially constant throughout all geometries 2: attribute variables are assumed to be spatially constant throughout all geometries 3: attribute variables are assumed to be spatially constant throughout all geometries 4: attribute variables are assumed to be spatially constant throughout all geometries 5: attribute variables are assumed to be spatially constant throughout all geometries

2. Hierarchical Modelling of Species Communities

We will use the probabilities and indices of influences calculated in Section 1 here. The aim is to obtain predictive models for the benthic communities, based on the abiotic parameters and the human activities.

HMSC models have been developped in a dedicated script, and the R workspace has been imported here.

First, we initiate the HMSC model with the chosen data, priors and parameters.

Here are the diagnostics to evaluate each model’s quality.

Human activities

Trace plots

Explanatory power

Confidence intervals

Variance partitioning

Habitat parameters

Trace plots

Explanatory power

Confidence intervals

Variance partitioning

All variables

Trace plots

Explanatory power

Confidence intervals

Variance partitioning

Finally, we can predict the values of our parameters within BSI.

Elliot Dreujou

2020-02-07